Vehicle behavior estimating device and vehicle behavior estimating method

Abstract

To provide a vehicle behavior estimating device and a vehicle behavior estimating method that can obtain information on estimation reliability based on the difficulty of estimation when estimating a vehicle behavior of a second vehicle which exists around a first vehicle.SOLUTION: A vehicle behavior estimating device acquires road information on which a first vehicle travels and information of a second vehicle, estimates a vehicle behavior of the second vehicle based on at least the information of the second vehicle and the road information, and calculates estimation reliability of the vehicle behavior of the second vehicle based on the difficulty of estimating the vehicle behavior of the second vehicle based on at least one of the information of the first vehicle, the information of the second vehicle, and the road information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a vehicle behavior estimation device and a vehicle behavior estimation method. [Background technology]

[0002] There is a technology that improves safety and comfort by predicting a lane change of another vehicle that cuts in front of the vehicle before the cut-in is completed and controlling the vehicle in advance. In the technology of Patent Document 1, the lane change of the other vehicle is predicted from the traveling state of the other vehicle, such as the detected position and speed of the other vehicle. In addition, the judgment criteria are changed depending on the distance between the vehicle and the other vehicle. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-142901 Summary of the Invention [Problem to be solved by the invention]

[0004] However, depending on the detection state of the running state of the other vehicle and the road state, the difficulty of estimating the vehicle behavior of the other vehicle changes, and the reliability of the estimation result changes. For example, when the detection state of the sensor that detects the running state of the other vehicle is poor, or when the visibility of the other vehicle from the own vehicle is poor, the difficulty of the estimation increases and the reliability of the estimation result decreases.

[0005] However, in the technology of Patent Document 1, a lane change is estimated from the detected traveling state of other vehicles, but the difficulty of the estimation is not taken into consideration. Therefore, even if the difficulty of the estimation is high and the reliability of the estimation result is low, the estimation result is still used.

[0006] Therefore, an object of the present disclosure is to provide a vehicle behavior estimation device and a vehicle behavior estimation method that are capable of obtaining information on the estimation reliability based on the difficulty of the estimation when estimating the vehicle behavior of a second vehicle that is present around a first vehicle. [Means for solving the problem]

[0007] A vehicle behavior estimation device according to the present disclosure includes: an information acquisition unit that acquires road information on which the first vehicle is traveling and information on surrounding vehicles present around the first vehicle; a second vehicle behavior estimation unit that sets a second vehicle, which is a target of vehicle behavior estimation, from among the surrounding vehicles, and estimates a vehicle behavior of the second vehicle based on at least information on the second vehicle and the road information; a reliability calculation unit that calculates an estimation reliability of a vehicle behavior of the second vehicle according to a degree of difficulty in estimating the vehicle behavior of the second vehicle based on at least one of information of the first vehicle, the second vehicle, and the road information; It is equipped with the following:

[0008] The vehicle behavior estimation method according to the present disclosure includes: an information acquisition step of acquiring road information on which the first vehicle is traveling and information on surrounding vehicles existing around the first vehicle; a second vehicle behavior estimating step of setting a second vehicle, which is a target of estimation of a vehicle behavior, from the surrounding vehicles, and estimating a vehicle behavior of the second vehicle based on at least information on the second vehicle and the road information; a reliability calculation step of calculating an estimation reliability of a vehicle behavior of the second vehicle according to a degree of difficulty in estimating the vehicle behavior of the second vehicle based on at least one of information of the first vehicle, the second vehicle, and the road information; It is equipped with the following: Effect of the Invention

[0009] According to the vehicle behavior estimation device and vehicle behavior estimation method of the present disclosure, the estimation reliability of the vehicle behavior of the second vehicle is calculated according to the difficulty level of estimating the vehicle behavior of the second vehicle based on at least one of the information of the first vehicle, the information of the second vehicle, and the road information, so that an evaluation index can be given to the estimation result of the vehicle behavior of the second vehicle, and the estimation result of the vehicle behavior of the second vehicle can be appropriately used. [Brief description of the drawings]

[0010] [Figure 1] 1 is a schematic block diagram of a vehicle behavior estimation device according to a first embodiment. [Diagram 2] 1 is a schematic hardware configuration diagram of a vehicle behavior estimation device according to a first embodiment. [Diagram 3] 1 is a schematic hardware configuration diagram of a vehicle behavior estimation device according to a first embodiment. [Figure 4] 3 is a diagram for explaining a coordinate system of a first vehicle and a road coordinate system of a second vehicle according to the first embodiment. FIG. [Diagram 5] FIG. 2 is a schematic diagram for explaining lane change of a second vehicle to the front of a first vehicle in the first embodiment. [Figure 6] FIG. 4 is a schematic diagram for explaining the calculation of the estimated reliability of each factor according to the first embodiment. [Figure 7] 4 is a flowchart for explaining processing of the vehicle behavior estimation device according to the first embodiment. [Figure 8] FIG. 11 is a schematic block diagram of a vehicle behavior estimation device according to a second embodiment. [Figure 9] 10 is a diagram for explaining a determination made by a vehicle behavior determining unit according to the second embodiment. FIG. [Figure 10] 10 is a diagram for explaining a determination made by a vehicle behavior determining unit according to the second embodiment. FIG. [Figure 11] 10 is a diagram for explaining a determination made by a vehicle behavior determining unit according to the second embodiment. FIG. [Figure 12] 10 is a flowchart for explaining processing of a vehicle behavior estimation device according to the second embodiment. [Figure 13]FIG. 11 is a schematic block diagram of a vehicle behavior estimation device according to a third embodiment. [Figure 14] 11 is a flowchart for explaining processing of a vehicle behavior estimation device according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] 1. First embodiment A vehicle behavior estimation device 1 according to the first embodiment will be described with reference to the drawings. In this embodiment, the vehicle behavior estimation device 1 is provided in a first vehicle.

[0012] As shown in FIG. 1, the first vehicle is equipped with a surroundings monitoring device 31, a position detection device 32, a vehicle state detection device 33, a map information database 34, a wireless communication device 35, a vehicle behavior estimation device 1, a drive control device 36, a power plant 8, an electric steering device 7, and an electric braking device 9, etc.

[0013] The periphery monitoring device 31 is a device such as a camera or radar that monitors the periphery of the first vehicle (at least the area in front of the first vehicle). The radar may be a millimeter wave radar, a laser radar, an ultrasonic radar, or the like. The wireless communication device 35 performs wireless communication with base stations, surrounding vehicles, roadside devices, and the like using a cellular wireless communication standard such as 4G or 5G.

[0014] The position detection device 32 is a device that detects the current position (latitude, longitude, altitude) of the first vehicle, and a GPS antenna that receives signals output from an artificial satellite such as a Global Navigation Satellite System (GNSS) is used. Note that the current position of the first vehicle may be detected by various methods such as a method using the lane number of the first vehicle, a map matching method, a dead reckoning method, a method using detection information around the first vehicle, and the like.

[0015] The map information database 34 stores road information such as road shape (e.g., the number of lanes, the position of each lane, the shape of each lane, the type of each lane, road type, speed limit, etc.), signs, traffic lights, etc. The shape of the lane includes the position, width, curvature, gradient (longitudinal gradient, lateral gradient), etc. of each point along the traveling direction. The map information database 34 is mainly composed of a storage device. The map information database 34 may be provided in a server outside the vehicle connected to a network, and the vehicle behavior estimation device 1 may obtain the necessary road information from the server outside the vehicle via the wireless communication device 35.

[0016] The drive control device 36 includes a power control device, a brake control device, an automatic steering control device, a light control device, etc. The power control device controls the output of a power machine 8 such as an internal combustion engine or a motor. The brake control device controls the braking operation of an electric brake device 9. The automatic steering control device controls the electric steering device 7. The light control device controls a direction indicator, a hazard lamp, etc.

[0017] The vehicle state detection device 33 is a detection device that detects a first vehicle state, which is a driving state and a traveling state of the first vehicle. In the present embodiment, the vehicle state detection device 33 detects the speed, acceleration, yaw rate, steering angle, lateral acceleration, etc. of the first vehicle as the traveling state of the first vehicle. For example, a speed sensor, an acceleration sensor, an angular velocity sensor, a steering angle sensor, etc. that detect the rotation speed of the wheels are provided as the vehicle state detection device 33.

[0018] As the driving state of the first vehicle, the acceleration / deceleration operation, the steering angle operation, and the lane change operation by the driver are detected. For example, an accelerator position sensor, a brake position sensor, a steering angle sensor (handle angle sensor), a steering torque sensor, a turn signal position switch, etc. are provided as the vehicle state detection device 33.

[0019] 1-1. Vehicle behavior estimation device 1 The vehicle behavior estimation device 1 includes functional units such as an information acquisition unit 51, a second vehicle behavior estimation unit 52, and a reliability calculation unit 53. Each function of the vehicle behavior estimation device 1 is realized by a processing circuit included in the vehicle behavior estimation device 1. Specifically, as shown in Fig. 2, the vehicle behavior estimation device 1 includes an arithmetic processing device 90 such as a CPU (Central Processing Unit), a storage device 91, an input / output device 92 that inputs and outputs external signals to the arithmetic processing device 90, and the like.

[0020] The arithmetic processing device 90 may be an ASIC (Application Specific Integrated Circuit), an IC (Integrated Circuit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), a GPU (Graphics Processing Unit), an AI (Artificial Intelligence) chip, various logic circuits, various signal processing circuits, etc. Also, the arithmetic processing device 90 may be a plurality of the same or different types, and each process may be shared and executed. As the storage device 91, various storage devices such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a hard disk, etc. are used.

[0021] The input / output device 92 includes a communication device, an A / D converter, an input / output port, a drive circuit, etc. The input / output device 92 is connected to the surroundings monitoring device 31, the position detection device 32, the vehicle state detection device 33, the map information database 34, the wireless communication device 35, the drive control device 36, etc., and communicates with these devices.

[0022] Each function of the functional units 51 to 53 of the vehicle behavior estimation device 1 is realized by the arithmetic processing device 90 executing software (programs) stored in the storage device 91 and cooperating with other hardware of the vehicle behavior estimation device 1, such as the storage device 91 and an input / output device 92. Note that setting data used by the functional units 51 to 53 is stored in the storage device 91, such as an EEPROM.

[0023] Alternatively, the vehicle behavior estimation device 1 may be provided with dedicated hardware 93 as a processing circuit, such as a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, a GPU, an AI chip, or a circuit combining these, as shown in Fig. 3. Each function of the vehicle behavior estimation device 1 will be described in detail below.

[0024] 1-1-1. Information acquisition section 51 The information acquisition unit 51 acquires road information on which the first vehicle is traveling. In this embodiment, the information acquisition unit 51 acquires road information around the first vehicle from the map information database 34 based on the position information of the first vehicle acquired from the position detection device 32. The acquired road information includes information such as the number of lanes, the position of each lane, the shape of each lane, the type of each lane, the road type, and the speed limit. The shape of the lane includes the position, width, curvature, and gradient (longitudinal gradient, horizontal gradient) of each point along the traveling direction.

[0025] In addition, the information acquisition unit 51 detects the shape and type of road dividing lines, etc. based on detection information of dividing lines such as white lines and road shoulders acquired from the perimeter monitoring device 31, and determines the shape, number of lanes, type of each lane, etc. based on the detected shape and type of road dividing lines, etc.

[0026] The information acquisition unit 51 acquires lane information corresponding to the lane in which the first vehicle is traveling, based on the position of the first vehicle. The information acquisition unit 51 also acquires lane information corresponding to the lane in which each of the surrounding vehicles is traveling, based on the position of each of the surrounding vehicles. The acquired lane information includes the shape, position, and type of the lane, and lane information of the surrounding lanes.

[0027] The information acquisition unit 51 acquires the state of surrounding vehicles existing around the first vehicle. In this embodiment, the information acquisition unit 51 acquires the position, moving direction, speed, acceleration, and the like of the surrounding vehicles based on the detection information acquired from the periphery monitoring device 31 and the position information of the first vehicle acquired from the position detection device 32. Furthermore, the information acquisition unit 51 acquires information on obstacles, pedestrians, signs, traffic regulations such as lane regulations, and the like in addition to the surrounding vehicles.

[0028] In this embodiment, the information acquisition unit 51 acquires the relative positions and relative speeds of surrounding vehicles and the like with respect to the first vehicle in a coordinate system of the first vehicle based on the current position of the first vehicle. As shown in Fig. 4, the coordinate system of the first vehicle is a coordinate system having an axis in the longitudinal direction X of the current first vehicle and an axis in the lateral direction Y of the first vehicle.

[0029] 1-1-2. Second vehicle behavior estimation unit 52 The second vehicle behavior estimation unit 52 sets a second vehicle as a target for estimating the vehicle behavior from among the surrounding vehicles, and estimates the vehicle behavior of the second vehicle based on at least information about the second vehicle and information about the road on which the first vehicle is traveling.

[0030] The second vehicle behavior estimation unit 52 estimates the vehicle behavior by sequentially setting, among the surrounding vehicles, vehicles that affect the traveling of the first vehicle as the second vehicle. For example, each surrounding vehicle traveling within a judgment distance range from the first vehicle in the traveling lane of the first vehicle and the adjacent lanes is set as the second vehicle. For each surrounding vehicle set as the second vehicle, the vehicle behavior is estimated, and the estimation reliability of the vehicle behavior is calculated. Note that the second vehicle may be limited to the surrounding vehicles traveling in each lane ahead of the first vehicle.

[0031] In this embodiment, the second vehicle behavior estimation unit 52 estimates the probability of lane change of the second vehicle as the vehicle behavior of the second vehicle. The probability of lane change to the left lane and the probability of lane change to the right lane are estimated separately. For example, the probability of lane change to the left lane, the probability of lane change to the right lane, and the probability of lane keeping are estimated so that the sum of these is 100%. In particular, as shown in FIG. 5, the configuration may be such that the probability of lane change of the second vehicle to the driving lane of the first vehicle and ahead of the first vehicle is estimated.

[0032] <Probability of lane change due to lateral movement of second vehicle> For example, the second vehicle behavior estimation unit 52 calculates information regarding the lateral movement of the second vehicle based on information about the second vehicle and road information, and estimates the probability of a lane change due to the lateral movement of the second vehicle based on the information regarding the lateral movement.

[0033] The second vehicle behavior estimation unit 52 calculates at least one of the following information regarding the lateral movement of the second vehicle: the lateral position, speed, acceleration, time change in position, time change in speed, and time change in acceleration of the second vehicle relative to the lane in which the second vehicle is traveling, and based on the calculated information regarding the lateral movement, the greater the tendency of the second vehicle to move laterally relative to the lane in which the second vehicle is traveling, the higher the estimated probability of a lane change due to lateral movement.

[0034] According to this configuration, the probability of a lane change due to lateral movement can be accurately estimated based on the information regarding the lateral movement of the second vehicle as described above.

[0035] 4, in this embodiment, the second vehicle behavior estimation unit 52 converts the relative position, relative speed, and relative acceleration of the second vehicle in the coordinate system of the first vehicle into the relative position, relative speed, and relative acceleration of the second vehicle in a coordinate system of the longitudinal direction S and lateral direction W of the lane in which the second vehicle is located (referred to as the road coordinate system of the second vehicle). The relative positions before and after the conversion include the longitudinal relative position and the lateral relative position in each coordinate system, the relative speeds before and after the conversion include the longitudinal relative speed and the lateral relative speed in each coordinate system, and the relative accelerations before and after the conversion include the longitudinal relative acceleration and the lateral relative acceleration in each coordinate system.

[0036] In the road coordinate system of the second vehicle, the tangent direction to the center line of the driving lane in which the second vehicle is traveling is taken as the longitudinal direction S, and the normal direction to the center line is taken as the lateral direction W. In addition, the position on the center line that is closest to the position of the second vehicle is taken as the origin.

[0037] The second vehicle behavior estimation unit 52 performs a rotational coordinate transformation based on the relative angle of the longitudinal direction S of the road coordinate system of the second vehicle with respect to the longitudinal direction X of the coordinate system of the first vehicle, and a movement transformation based on the relative position of the origin of the road coordinate system of the second vehicle with respect to the origin of the coordinate system of the first vehicle, on the relative position, relative speed, and relative acceleration of the second vehicle in the road coordinate system of the second vehicle. These rotational coordinate transformations and movement transformations are well-known techniques, and therefore their explanations are omitted.

[0038] The second vehicle behavior estimation unit 52 calculates time difference values ​​of the converted relative position, relative velocity, and relative acceleration in the lateral direction W, thereby calculating the amount of change over time of each of the converted relative position, relative velocity, and relative acceleration in the lateral direction W. For example, as the time difference value (amount of change over time), a difference value between a current value and a value a predetermined time ago, or a difference value between a current value and a filtered value (for example, a moving average value) is calculated.

[0039] <Use of learning models> The second vehicle behavior estimation unit 52 determines the probability of a lane change due to lateral movement of the second vehicle based on the information regarding the lateral movement of the second vehicle using a learning model that is trained to input information regarding the lateral movement of the second vehicle and output the probability of a lane change due to lateral movement.

[0040] For example, a logistic regression model is used as the learning model. The parameters of the logistic regression model are adjusted in advance using a data set of information on the lateral movement of the second vehicle and whether or not there is a lane change, which is collected in advance, so that the presence or absence of a lane change can be separated from the information on the lateral movement of the second vehicle. The presence of a lane change means that the probability of a lane change is 100%, and the absence of a lane change means that the probability of a lane change is 0%.

[0041] Alternatively, various known learning models such as a neural network may be used as the learning model. Also, instead of the presence or absence (100% or 0%) of a lane change, the probability of a lane change may be estimated.

[0042] The second vehicle behavior estimation unit 52 may estimate the probability of the second vehicle changing lanes based on a comparison result between each piece of information related to the lateral movement of the second vehicle and a threshold value set for each piece of information.

[0043] In addition, the second vehicle behavior estimation unit 52 estimates the relative position of the second vehicle after the lane change relative to the first vehicle, i.e., the relative position of the lane change destination, based on information regarding the lateral movement of the second vehicle and the relative position and relative speed between the first vehicle and the second vehicle.

[0044] <Probability correction based on the surrounding environment of the second vehicle> The second vehicle behavior estimation unit 52 may correct the probability of lane change due to lateral movement of the second vehicle depending on the relationship between the second vehicle and the surrounding environment of the second vehicle. For example, when there is a state on the left side of the second vehicle that is an obstacle to lane change (for example, there is no adjacent lane on the left side, or an obstacle for lane change exists in the adjacent lane on the left side), the second vehicle behavior estimation unit 52 corrects the probability of lane change to the left lane to 0%, and increases each probability of lane change to the right lane and the probability of lane keeping so that the sum of the probabilities becomes 100%. The same applies to the right lane.

[0045] <Probability of lane changing due to triggering factors> The second vehicle behavior estimation unit 52 may estimate the probability of a lane change due to an inducing factor that induces the second vehicle to change lane due to the relationship between the second vehicle and the surrounding environment of the second vehicle, and calculate the probability of a lane change by the second vehicle as the vehicle behavior of the second vehicle by taking a weighted average of the probability of a lane change due to lateral movement and the probability of a lane change due to an inducing factor.

[0046] A lane change of the second vehicle is induced by merging from a merging lane to a main lane. The probability of lane change due to merging is determined by a method different from lane change due to normal lateral movement. For example, the second vehicle behavior estimation unit 52 predicts whether the second vehicle will merge around (for example, in front of or behind) the first vehicle based on at least the relative position and relative speed between the second vehicle traveling in the merging lane and the first vehicle traveling on the main lane, and the shape of the merging lane (positions of the start and end points of the merging lane, etc.), and if the second vehicle will merge, predicts the merging relative position of the second vehicle with respect to the first vehicle. As an example of a case where the second vehicle does not merge around the first vehicle, the second vehicle may decelerate or stop temporarily near the end point of the merging lane. Various known methods are used for merging prediction.

[0047] If the second vehicle behavior estimation unit 52 predicts that the second vehicle will merge around the first vehicle (for example, within a judgment distance range in front of or behind the first vehicle), it sets the probability of lane change due to merging to 100%, and if it predicts that the second vehicle will not merge around the first vehicle, it sets the probability of lane change due to merging to 0%. If it is possible to continuously predict the probability that the second vehicle will merge around the first vehicle, the probability of lane change due to merging is continuously set within a range from 0% to 100%.

[0048] When the second vehicle is traveling in a merging lane and the probability of changing lanes due to merging is estimated, the second vehicle behavior estimation unit 52 may calculate the probability of the second vehicle changing lanes as the vehicle behavior of the second vehicle by taking a weighted average of the probability of changing lanes due to lateral movement and the probability of changing lanes due to merging, as shown in the following equation. Probability of lane change = Probability of lane change by lateral movement × α + Probability of lane change by merging × (1-α)

[0049] Here, α is the weight of the weighted average, and is set to an appropriate value between 0 and 1. If the second vehicle is traveling in a merging lane and the probability of lane change due to lateral movement cannot be estimated, α is set to 0, and if the second vehicle is not traveling in a merging lane and the probability of lane change due to merging cannot be estimated, α is set to 1.

[0050] 1-1-3. Reliability calculation unit 53 The reliability calculation unit 53 calculates the estimation reliability of the vehicle behavior of the second vehicle based on the difficulty of estimating the vehicle behavior of the second vehicle, based on at least one of the information of the first vehicle, the information of the second vehicle, and the road information.

[0051] For example, the more difficult it is to estimate the vehicle behavior of the second vehicle, the lower the estimation reliability. An evaluation index can be given to the estimation result of the vehicle behavior of the second vehicle by the second vehicle behavior estimating unit 52.

[0052] The reliability calculation unit 53 calculates the estimation reliability based on at least one of the factors contributing to the estimation difficulty, which are the distance between the first vehicle and the second vehicle, the road curvature related to the detection of the second vehicle, the road gradient related to the detection of the second vehicle, and the degree of overlap between the second vehicle and other vehicles related to the detection of the second vehicle.

[0053] As the distance between the first vehicle and the second vehicle increases, the accuracy of detection of the second vehicle by the periphery monitoring device 31 decreases, so the degree of difficulty of estimation increases, and the estimation reliability decreases. As the road curvature related to the detection of the second vehicle increases, the visibility of the road in front of or behind the first vehicle decreases, or the lateral fluctuation of the second vehicle increases, making it difficult for the periphery monitoring device 31 to detect the second vehicle, so the degree of difficulty of estimation increases, and the estimation reliability decreases. It is sufficient to use the road curvature corresponding to the road portion between the first vehicle and the second vehicle or the road portion of the second vehicle, and for example, the average value of the road curvature of the road portion between the first vehicle and the second vehicle, or the road curvature of the road portion of the second vehicle is used.

[0054] As the road gradient related to the detection of the second vehicle increases, the visibility of the road in front or behind the first vehicle becomes poor, or as the lateral gradient increases, the lateral fluctuation of the second vehicle becomes large, making it difficult for the periphery monitoring device 31 to detect the second vehicle, and therefore the degree of difficulty of estimation increases, lowering the estimation reliability. It is sufficient to use the road gradient corresponding to the road portion between the first vehicle and the second vehicle, and for example, the average value of the road gradient of the road portion between the first vehicle and the second vehicle, or the road gradient of the road portion of the second vehicle, is used.

[0055] As the degree of overlap between the second vehicle and other vehicles in relation to the detection of the second vehicle increases, the portion of the second vehicle detected by the surroundings monitoring device 31 becomes smaller, making it more difficult to detect the second vehicle accurately, thereby increasing the difficulty of estimation and decreasing the reliability of estimation.

[0056] In this embodiment, the reliability calculation unit 53 calculates the estimation reliability based on the detection state of the sensor that detects the second vehicle as a factor that contributes to the estimation difficulty level. The detection state of the sensor includes one or more of reliability information of the detection result output from each sensor that detects the second vehicle, the number of sensors that can use the detection results among the multiple sensors for detecting the second vehicle, the presence or absence of outliers in the detection values ​​of the multiple sensors for detecting the second vehicle, and the presence or absence of temporal discontinuity in the detection values ​​of the multiple sensors for detecting the second vehicle.

[0057] As sensors for detecting the second vehicle, a camera and a radar (millimeter wave radar, laser radar, ultrasonic radar, etc.) of the perimeter monitoring device 31 are used. Regarding reliability information of the detection result, in the case of a camera, the reliability information of the detection result from an image changes depending on the imaging conditions (e.g., imaging conditions due to brightness, backlight, weather (fog, rain, snow), etc.). In the case of a radar, the reliability information of the detection result from radar reflection changes depending on the conditions of the subject (e.g., the reflectivity of the detected object, conditions due to weather (fog, rain, snow), etc.).

[0058] As the number of sensors whose detection results can be used decreases, the detection accuracy of the second vehicle decreases, and the difficulty of estimation increases, lowering the reliability of estimation. For example, the detection results of a particular sensor may become unusable due to a sensor failure or deterioration of the detection state of the sensor due to some factor.

[0059] If, among the information on the second vehicle detected by each sensor, there is detection information from a sensor that deviates from the detection information of other sensors by more than a predetermined value, the difficulty of estimation increases due to the presence of an outlier, thereby reducing the reliability of the estimation.

[0060] If the information about the second vehicle detected by each sensor becomes discontinuous over time, it can be determined that the detection accuracy has deteriorated due to some factor, and therefore the difficulty of estimation increases, lowering the reliability of estimation.

[0061] The reliability calculation unit 53 lowers the estimation reliability when the estimation result of the past vehicle behavior by the second vehicle behavior estimation unit 52 is erroneous.

[0062] For example, the reliability calculation unit 53 reduces the estimation reliability when the second vehicle does not change lanes even after a determination period has elapsed after the probability of lane change of the second vehicle estimated by the second vehicle behavior estimation unit 52 becomes equal to or greater than a predetermined value. Alternatively, the reliability calculation unit 53 reduces the estimation reliability when the second vehicle changes lanes in a state in which the probability of lane change of the second vehicle is estimated by the second vehicle behavior estimation unit 52 to be equal to or less than a predetermined value. The reliability calculation unit 53 may continuously reduce the estimation reliability when a state in which the estimation result of the past vehicle behavior is erroneous continues, and continuously increase the estimation reliability when a state in which the estimation result of the past vehicle behavior is correct continues.

[0063] <Overall evaluation of each factor> In this embodiment, the reliability calculation unit 53 calculates the estimation reliability of each factor that contributes to the estimation difficulty level, and calculates the final estimation reliability based on the estimation reliability of each factor. That is, the estimation reliability of each factor is evaluated comprehensively to calculate the final estimation reliability.

[0064] For example, the reliability calculation unit 53 multiplies the estimated reliability R of each factor by the sum as shown in the following formula to calculate the final estimated reliability Rall. Rall = R1 x R2 x R3 x R4 x R5 x R6 Here, for example, R1 is an estimation reliability calculated based on the distance between the first vehicle and the second vehicle. R2 is an estimation reliability calculated based on the road curvature related to the detection of the second vehicle. R3 is an estimation reliability calculated based on the road gradient related to the detection of the second vehicle. R4 is an estimation reliability calculated based on the degree of overlap between the second vehicle and another vehicle. R5 is an estimation reliability calculated based on the detection state of the sensor that detects the second vehicle, and may be calculated for each type of the detection state of the sensor, or may be calculated by comprehensively evaluating multiple types of the detection state of the sensor. R6 is an estimation reliability calculated based on an error in the estimation result of the past vehicle behavior. All of these R1 to R6 may not be used, and one or more of R1 to R6 may be used.

[0065] As shown in FIG. 6, as the input value U of each factor, such as distance, road curvature, road gradient, degree of overlap, degree of deterioration of the sensor detection state, degree of error of the estimation result, etc., increases, the estimation reliability R of each factor decreases from 1 to 0. The highest value of the estimation reliability R is 1, and the lowest value of the estimation reliability R is 0. The estimation reliability R is set to 1 until the input value U of each factor exceeds a threshold value, and in a normal state, the estimation reliability R of each factor is kept at a high value and does not decrease unnecessarily. The estimation reliability R of each factor is calculated using map data or a formula preset for each factor.

[0066] Alternatively, the reliability calculation unit 53 may calculate the final estimated reliability Rall based on the estimated reliability R of each factor by a calculation method other than the summation. For example, a high-order formula, a neural network, or the like is used.

[0067] The estimated vehicle behavior of the second vehicle (in this example, the probability of the second vehicle changing lanes) and the estimated reliability of the vehicle behavior of the second vehicle are transmitted to an external device or, as in the second and third embodiments described below, to other processing units of the vehicle behavior estimation device 1, and are used for various types of processing.

[0068] <Flowchart> 7 is a schematic flowchart illustrating the process (vehicle behavior estimation method) of the vehicle behavior estimation device 1 according to this embodiment. The process in FIG. 7 is executed, for example, at every predetermined calculation cycle.

[0069] In step S01, as described above, the information acquisition unit 51 acquires information about the road on which the first vehicle is traveling and information about surrounding vehicles existing around the first vehicle.

[0070] In step S02, as described above, the second vehicle behavior estimation unit 52 sets a second vehicle, the vehicle behavior of which is to be estimated, from the surrounding vehicles, and estimates the vehicle behavior of the second vehicle based on at least the information of the second vehicle and the information of the road on which the first vehicle is traveling. In this embodiment, the second vehicle behavior estimation unit 52 estimates the probability of the second vehicle changing lanes as the vehicle behavior of the second vehicle.

[0071] In step S03, as described above, the reliability calculation unit 53 calculates the estimation reliability of the vehicle behavior of the second vehicle based on the difficulty of estimating the vehicle behavior of the second vehicle, based on at least one of the information of the first vehicle, the information of the second vehicle, and the road information.

[0072] 2. Second embodiment Next, a vehicle behavior estimation device 1 according to a second embodiment will be described. Description of components similar to those of the first embodiment will be omitted. The basic configuration of the vehicle behavior estimation device 1 according to the present embodiment is similar to that of the first embodiment, but differs from the first embodiment in that the vehicle behavior estimation device 1 further includes a vehicle behavior determination unit 54 as shown in FIG.

[0073] The vehicle behavior determination unit 54 ultimately determines whether or not the second vehicle will execute the estimated vehicle behavior based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit 52 and the estimation reliability calculated by the reliability calculation unit 53.

[0074] According to this configuration, a final determination is made as to whether or not the second vehicle will execute the estimated vehicle behavior taking into account the estimation reliability, thereby improving the final prediction accuracy of the vehicle behavior of the second vehicle.

[0075] In this embodiment, the vehicle behavior determination unit 54 finally determines whether or not the second vehicle will perform the estimated lane change based on the probability of the second vehicle changing lanes estimated as the vehicle behavior of the second vehicle by the second vehicle behavior estimation unit 52 and the estimation reliability calculated by the reliability calculation unit 53.

[0076] For example, as shown in Fig. 9, the vehicle behavior determination unit 54 finally determines that the second vehicle will execute the estimated lane change when the probability of the lane change of the second vehicle exceeds a first threshold and the estimation reliability exceeds a second threshold, and finally determines that the second vehicle will not execute the estimated lane change in other cases. In Fig. 9, a lane change probability of 100% is represented by 1.

[0077] Alternatively, as shown in Fig. 10, the vehicle behavior determination unit 54 sets a threshold value based on the estimation reliability, and when the probability of the second vehicle changing lanes exceeds the threshold value, it finally determines that the second vehicle will change lanes as estimated, and otherwise it finally determines that the second vehicle will not change lanes as estimated. As the estimation reliability decreases, the first threshold value is increased.

[0078] Alternatively, as shown in FIG. 11, the vehicle behavior determination unit 54 finally determines that the second vehicle will perform the estimated lane change if the multiplied value of the probability of the second vehicle changing lanes and the estimation reliability exceeds a threshold value, and finally determines that the second vehicle will not perform the estimated lane change in any other cases.

[0079] Alternatively, the boundary line (threshold) between the probability of the second vehicle's lane change and the estimation reliability for determining whether the second vehicle will perform the estimated lane change may be set to an arbitrary shape.

[0080] The final judgment result of whether or not the estimated vehicle behavior of the second vehicle will be performed (in this example, the final judgment result of whether or not the estimated lane change of the second vehicle will be performed) is transmitted to an external device or to another processing unit of the vehicle behavior estimation device 1 and used for various processes. For example, the vehicle behavior of the second vehicle that is finally judged to be performed may be notified to the driver of the first vehicle via a human interface device such as a display device or a speaker. Furthermore, the vehicle control unit 55 described in the third embodiment may calculate the control amount of the first vehicle based on the vehicle behavior of the second vehicle that is finally judged to be performed.

[0081] <Flowchart> 12 is a schematic flowchart illustrating the process (vehicle behavior estimation method) of the vehicle behavior estimation device 1 according to this embodiment. The process in FIG. 12 is executed, for example, at every predetermined calculation cycle.

[0082] Steps S11 to S13 are similar to steps S01 to S03 in the first embodiment of FIG. 7, and therefore the description thereof will be omitted.

[0083] In step S14, as described above, the vehicle behavior determination unit 54 finally determines whether or not the second vehicle will execute the estimated vehicle behavior, based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit 52 and the estimation reliability calculated by the reliability calculation unit 53. In this embodiment, the vehicle behavior determination unit 54 finally determines whether or not the second vehicle will execute the estimated lane change, based on the probability of the lane change of the second vehicle estimated as the vehicle behavior of the second vehicle by the second vehicle behavior estimation unit 52 and the estimation reliability calculated by the reliability calculation unit 53.

[0084] 3. Third embodiment Next, a vehicle behavior estimation device 1 according to embodiment 3 will be described. Description of components similar to those of embodiment 1 will be omitted. The basic configuration of the vehicle behavior estimation device 1 according to this embodiment is similar to that of embodiment 1, but differs from embodiment 1 in that the vehicle behavior estimation device 1 further includes a vehicle control unit 55, as shown in FIG.

[0085] The vehicle control unit 55 calculates a control amount for the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit 52 and the estimation reliability calculated by the reliability calculation unit 53.

[0086] According to this configuration, the control amount of the first vehicle is calculated based on the estimated vehicle behavior of the second vehicle, taking into account the estimation reliability, so that the calculation accuracy of the control amount of the first vehicle can be improved.

[0087] In this embodiment, the vehicle control unit 55 calculates the control amount of the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit 52, and changes the magnitude of the calculated control amount of the first vehicle based on the estimation reliability calculated by the reliability calculation unit 53.

[0088] For example, the vehicle control unit 55 reduces the magnitude of the calculated control amount of the first vehicle as the estimation reliability decreases. The control amount may be reduced stepwise or continuously in response to the decrease in the estimation reliability. With this configuration, the control amount of the first vehicle is prevented from increasing based on the vehicle behavior with low estimation reliability, unnecessary vehicle control is prevented from being performed, and discomfort felt by the driver of the first vehicle can be reduced.

[0089] In this embodiment, the probability of lane change of the second vehicle is estimated as the vehicle behavior of the second vehicle. The vehicle control unit 55 determines whether or not control of the first vehicle is necessary based on the probability of lane change of the second vehicle. When the second vehicle is in the driving lane of the first vehicle, changes lanes before or after the first vehicle, and the probability of lane change of the second vehicle exceeds a threshold, the vehicle control unit 55 determines that control of the first vehicle is necessary, and otherwise determines that control of the first vehicle is not necessary. Alternatively, similar to the vehicle behavior determination unit 54 of the second embodiment, the vehicle control unit 55 may determine whether or not the second vehicle executes the estimated lane change based on the probability of lane change of the second vehicle and the estimation reliability, determine that the lane change will be executed, and determine that control of the first vehicle is necessary when the second vehicle is in the driving lane of the first vehicle, changes lanes before or after the first vehicle, and otherwise determine that control of the first vehicle is not necessary.

[0090] When it is determined that control of the first vehicle is necessary, the vehicle control unit 55 calculates the control amount of the first vehicle based on the prediction result of the lane change of the second vehicle. At this time, the vehicle control unit 55 reduces the magnitude of the calculated control amount of the first vehicle as the estimation reliability decreases. Note that, similarly to the vehicle behavior determination unit 54 of the second embodiment, when it is determined whether or not to execute a lane change based on the probability of a lane change and the estimation reliability, the vehicle control unit 55 does not need to change the magnitude of the control amount of the first vehicle based on the estimation reliability.

[0091] For example, when the second vehicle is in the lane in which the first vehicle is traveling and is predicted to change lanes in front of or behind the first vehicle, the vehicle control unit 55 calculates the change amounts of the target output torque and the target braking force to increase or decrease the speed of the first vehicle based on the relative positions and relative speeds of the first and second vehicles so that the inter-vehicle distance between the first and second vehicles is kept equal to or greater than a set distance. As the estimation reliability decreases, the vehicle control unit 55 reduces the maximum values ​​of the calculated change amounts of the target output torque and the target braking force.

[0092] The vehicle control unit 55 transmits the changed target output torque and target braking force to a power control device and a brake control device serving as the drive control device 36. Then, the power control device controls the output torque of the power machine 8 such as an internal combustion engine or a motor according to the target output torque. Also, the brake control device controls the brake operation of the electric brake device 9 according to the target braking force.

[0093] Alternatively, when the second vehicle is in the driving lane of the first vehicle and is predicted to change lanes in front of or behind the first vehicle, and it is determined that the first vehicle will change lanes to avoid the second vehicle, the vehicle control unit 55 may calculate a target steering angle for changing lanes. The vehicle control unit 55 transmits the target steering angle to the automatic steering control device, and the automatic steering control device controls the electric steering device 7 so that the steering angle follows the target steering angle.

[0094] Alternatively, in order to perform more advanced automatic driving, the vehicle control unit 55 may generate a time-series target driving trajectory based on the estimated vehicle behavior of the second vehicle and the estimation reliability. The time-series target driving trajectory is a time-series driving plan including a target position, a target traveling direction, a target speed, a target acceleration, and the like of the first vehicle at each future time. For example, when increasing the speed of the first vehicle, the vehicle control unit 55 increases the target speed and the target acceleration at each future time. At this time, the amount of increase is reduced as the estimation reliability decreases. The vehicle control unit 55 controls the vehicle so that the first vehicle runs following the target driving trajectory. For example, the vehicle control unit 55 determines a target output torque, a target braking force, a target steering angle, an operation command for a direction indicator, and the like, and transmits each determined command value to a power control unit, a brake control unit, an automatic steering control unit, a light control unit, and the like as the drive control unit 36.

[0095] <Flowchart> 14 is a schematic flowchart illustrating the process (vehicle behavior estimation method) of the vehicle behavior estimation device 1 according to this embodiment. The process in FIG. 14 is executed, for example, at every predetermined calculation cycle.

[0096] Steps S21 to S23 are similar to steps S01 to S03 in the first embodiment of FIG. 7, and therefore the description thereof will be omitted.

[0097] In step S24, as described above, the vehicle control unit 55 calculates the control amount of the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit 52 and the estimation reliability calculated by the reliability calculation unit 53. In this embodiment, the vehicle control unit 55 calculates the control amount of the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit 52, and changes the magnitude of the calculated control amount of the first vehicle based on the estimation reliability calculated by the reliability calculation unit 53.

[0098] <Other embodiments> In the above-described embodiments, the second vehicle behavior estimation unit 52 estimates the probability of lane change of the second vehicle as the vehicle behavior of the second vehicle. However, the second vehicle behavior estimation unit 52 may estimate various vehicle behaviors, such as deceleration, acceleration, stopping, etc., other than the probability of lane change of the second vehicle as the vehicle behavior of the second vehicle.

[0099] Summary of Aspects of the Disclosure Various aspects of the present disclosure are summarized below as appendices. (Appendix 1) an information acquisition unit that acquires road information on which the first vehicle is traveling and information on surrounding vehicles present around the first vehicle; a second vehicle behavior estimation unit that sets a second vehicle, which is a target of vehicle behavior estimation, from among the surrounding vehicles, and estimates a vehicle behavior of the second vehicle based on at least information on the second vehicle and the road information; a reliability calculation unit that calculates an estimation reliability of a vehicle behavior of the second vehicle according to a degree of difficulty in estimating the vehicle behavior of the second vehicle based on at least one of information of the first vehicle, the second vehicle, and the road information; A vehicle behavior estimation device comprising:

[0100] (Appendix 2) The vehicle behavior estimation device described in Appendix 1, wherein the second vehicle behavior estimation unit calculates information regarding the lateral movement of the second vehicle based on information about the second vehicle and the road information, and estimates a probability of a lane change due to the lateral movement of the second vehicle as the vehicle behavior of the second vehicle based on the information regarding the lateral movement.

[0101] (Appendix 3) the second vehicle behavior estimation unit calculates information regarding a lateral movement of the second vehicle based on information about the second vehicle and the road information, and estimates a probability of a lane change due to the lateral movement of the second vehicle based on the information about the lateral movement; Estimating a probability of lane change due to an inducement factor that induces a lane change of the second vehicle due to a relationship between the second vehicle and a surrounding environment of the second vehicle; A vehicle behavior estimation device as described in Appendix 1, which calculates the probability of lane changing of the second vehicle as the vehicle behavior of the second vehicle by taking a weighted average of the probability of lane changing due to the lateral movement and the probability of lane changing due to the inducement factor.

[0102] (Appendix 4) The vehicle behavior estimation device described in Appendix 2 or 3, wherein the second vehicle behavior estimation unit calculates, as information regarding the lateral movement of the second vehicle, at least one piece of information including a lateral position, a speed, an acceleration, a time change in position, a time change in speed, and a time change in acceleration of the second vehicle relative to the lane in which the second vehicle is traveling, and increases the estimated probability of a lane change due to the lateral movement based on the calculated information regarding the lateral movement, the greater the tendency of the second vehicle to move laterally relative to the lane in which the second vehicle is traveling.

[0103] (Appendix 5) The vehicle behavior estimation device according to any one of Appendices 2 to 4, wherein the second vehicle behavior estimation unit determines the probability of a lane change due to lateral movement of the second vehicle based on the information regarding the lateral movement of the second vehicle using a learning model trained to input information regarding the lateral movement of the second vehicle and output the probability of a lane change due to the lateral movement of the second vehicle.

[0104] (Appendix 6) The vehicle behavior estimation device according to any one of appendixes 1 to 5, wherein the reliability calculation unit calculates the estimation reliability based on at least one of the following factors contributing to the estimation difficulty: a distance between the first vehicle and the second vehicle, a road curvature related to the detection of the second vehicle, a road gradient related to the detection of the second vehicle, and a degree of overlap between the second vehicle and other vehicles related to the detection of the second vehicle.

[0105] (Appendix 7) the reliability calculation unit calculates the estimation reliability based on at least a detection state of a sensor that detects a second vehicle as a factor contributing to the estimation difficulty level; The vehicle behavior estimation device according to any one of appendixes 1 to 6, wherein the detection states of the sensors include one or more of: reliability information of detection results output from each sensor detecting the second vehicle; a number of sensors among the plurality of sensors for detecting the second vehicle whose detection results can be used; presence or absence of outliers in detection values ​​of the plurality of sensors for detecting the second vehicle; and presence or absence of temporal discontinuity in detection values ​​of the plurality of sensors for detecting the second vehicle.

[0106] (Appendix 8) The vehicle behavior estimation device according to any one of claims 1 to 7, wherein the reliability calculation unit reduces the estimation reliability when a past estimation result of the vehicle behavior by the second vehicle behavior estimation unit is erroneous.

[0107] (Appendix 9) The vehicle behavior estimation device according to any one of appendix 1 to 8, further comprising a vehicle behavior determination unit that finally determines whether or not the second vehicle will execute the estimated vehicle behavior, based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit and the estimation reliability calculated by the reliability calculation unit.

[0108] (Appendix 10) The vehicle behavior determination unit finally determines whether or not the second vehicle will execute the estimated lane change based on the probability of the second vehicle changing lanes estimated as the vehicle behavior of the second vehicle by the second vehicle behavior estimation unit and the estimation reliability calculated by the reliability calculation unit.

[0109] (Appendix 11) 11. The vehicle behavior estimation device according to any one of claims 1 to 10, further comprising a vehicle control unit that calculates a control amount of a first vehicle based on the vehicle behavior of a second vehicle estimated by the second vehicle behavior estimation unit and the estimation reliability calculated by the reliability calculation unit.

[0110] (Appendix 12) The vehicle control unit calculates the control amount of the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit, and changes a magnitude of the calculated control amount of the first vehicle based on the estimation reliability calculated by the reliability calculation unit.

[0111] (Appendix 13) an information acquisition step of acquiring road information on which the first vehicle is traveling and information on surrounding vehicles existing around the first vehicle; a second vehicle behavior estimating step of setting a second vehicle, which is a target of estimation of a vehicle behavior, from the surrounding vehicles, and estimating a vehicle behavior of the second vehicle based on at least information on the second vehicle and the road information; a reliability calculation step of calculating an estimation reliability of a vehicle behavior of the second vehicle according to a degree of difficulty in estimating the vehicle behavior of the second vehicle based on at least one of information of the first vehicle, the second vehicle, and the road information; A vehicle behavior estimation method comprising:

[0112] In the present disclosure, various exemplary embodiments and examples are described, but various features, aspects, and functions described in one or more embodiments are not limited to the application of a specific embodiment, but can be applied to the embodiments alone or in various combinations. Therefore, countless modifications not illustrated are expected within the scope of the technology disclosed in the present disclosure specification. For example, the modification, addition, or omission of at least one component, and the extraction and combination of at least one component with components of other embodiments are included. [Explanation of symbols]

[0113] 1: vehicle behavior estimation device, 51: information acquisition unit, 52: second vehicle behavior estimation unit, 53: reliability calculation unit, 54: vehicle behavior determination unit, 55: vehicle control unit

Claims

1. an information acquisition unit that acquires road information on which the first vehicle is traveling and information on surrounding vehicles present around the first vehicle; a second vehicle behavior estimation unit that sets a second vehicle, which is a target of vehicle behavior estimation, from among the surrounding vehicles, and estimates a vehicle behavior of the second vehicle based on at least information on the second vehicle and the road information; a reliability calculation unit that calculates an estimation reliability of a vehicle behavior of the second vehicle according to a degree of difficulty in estimating the vehicle behavior of the second vehicle based on at least one of information of the first vehicle, the second vehicle, and the road information; A vehicle behavior estimation device comprising:

2. 2. The vehicle behavior estimation device according to claim 1, wherein the second vehicle behavior estimation unit calculates information regarding a lateral movement of the second vehicle based on information about the second vehicle and the road information, and estimates a probability of a lane change due to the lateral movement of the second vehicle as the vehicle behavior of the second vehicle based on the information regarding the lateral movement.

3. the second vehicle behavior estimation unit calculates information regarding a lateral movement of the second vehicle based on information about the second vehicle and the road information, and estimates a probability of a lane change due to the lateral movement of the second vehicle based on the information regarding the lateral movement; Estimating a probability of lane change due to an inducement factor that induces a lane change of the second vehicle due to a relationship between the second vehicle and a surrounding environment of the second vehicle; The vehicle behavior estimation device according to claim 1 , further comprising: a weighted average of the probability of lane changing due to the lateral movement and the probability of lane changing due to the inducement factor to calculate the probability of lane changing of the second vehicle as the vehicle behavior of the second vehicle.

4. 4. The vehicle behavior estimation device according to claim 2 or 3, wherein the second vehicle behavior estimation unit calculates, as the information regarding the lateral movement of the second vehicle, at least one piece of information including a lateral position, a speed, an acceleration, a time change in position, a time change in speed, and a time change in acceleration of the second vehicle relative to the lane in which the second vehicle is traveling, and increases the estimated probability of a lane change due to the lateral movement based on the calculated information regarding the lateral movement, the greater the tendency of the second vehicle to move laterally relative to the lane in which the second vehicle is traveling.

5. 4. The vehicle behavior estimation device according to claim 2 or 3, wherein the second vehicle behavior estimation unit determines the probability of a lane change due to lateral movement of the second vehicle based on the information regarding the lateral movement of the second vehicle using a learning model that is trained to receive information regarding the lateral movement of the second vehicle and output the probability of the lane change due to the lateral movement.

6. 4. The vehicle behavior estimation device according to claim 1, wherein the reliability calculation unit calculates the estimation reliability based on at least one of the following factors contributing to the estimation difficulty: a distance between the first vehicle and the second vehicle, a road curvature related to the detection of the second vehicle, a road gradient related to the detection of the second vehicle, and a degree of overlap between the second vehicle and other vehicles related to the detection of the second vehicle.

7. the reliability calculation unit calculates the estimation reliability based on at least a detection state of a sensor that detects a second vehicle as a factor contributing to the estimation difficulty level; 4. The vehicle behavior estimation device according to claim 1, wherein the detection states of the sensors include one or more of: reliability information of the detection results output from each sensor detecting the second vehicle; the number of sensors among the plurality of sensors for detecting the second vehicle whose detection results can be used; the presence or absence of outliers in the detection values ​​of the plurality of sensors for detecting the second vehicle; and the presence or absence of temporal discontinuity in the detection values ​​of the plurality of sensors for detecting the second vehicle.

8. The vehicle behavior estimation device according to claim 1 , wherein the reliability calculation unit reduces the estimation reliability when a past estimation result of the vehicle behavior by the second vehicle behavior estimation unit is erroneous.

9. 4. The vehicle behavior estimation device according to claim 1, further comprising a vehicle behavior determination unit that finally determines whether or not the second vehicle will execute the estimated vehicle behavior, based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit and the estimation reliability calculated by the reliability calculation unit.

10. 10. The vehicle behavior estimation device according to claim 9, wherein the vehicle behavior determination unit finally determines whether or not the second vehicle will execute the estimated lane change, based on a probability of the second vehicle changing lanes estimated as the vehicle behavior of the second vehicle by the second vehicle behavior estimation unit and the estimation reliability calculated by the reliability calculation unit.

11. 4. The vehicle behavior estimation device according to claim 1, further comprising a vehicle control unit that calculates a control amount of the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit and the estimation reliability calculated by the reliability calculation unit.

12. The vehicle behavior estimation device according to claim 11, wherein the vehicle control unit calculates the control amount of the first vehicle based on the vehicle behavior of the second vehicle estimated by the second vehicle behavior estimation unit, and changes a magnitude of the calculated control amount of the first vehicle based on the estimation reliability calculated by the reliability calculation unit.

13. an information acquisition step of acquiring road information on which the first vehicle is traveling and information on surrounding vehicles existing around the first vehicle; a second vehicle behavior estimating step of setting a second vehicle, which is a target of estimation of a vehicle behavior, from among the surrounding vehicles, and estimating a vehicle behavior of the second vehicle based on at least information on the second vehicle and the road information; a reliability calculation step of calculating an estimation reliability of a vehicle behavior of the second vehicle according to a degree of difficulty in estimating the vehicle behavior of the second vehicle based on at least one of information of the first vehicle, the second vehicle, and the road information; A vehicle behavior estimation method comprising:

Images